mcp-turtle-noir

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the answer format (four judgments and progress) and that it's a yes/no style question, but does not mention side effects, authentication, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences conveying the tool's purpose and response format with no extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple question-asking tool with two parameters and no output schema, the description covers the key behavior and response. It could mention that a session must be started first, but the required session_id parameter implies that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with both parameters described. The description adds minor nuance by specifying 'yes/no style' for the question parameter, but does not significantly extend beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the verb 'ask' and resource 'one yes/no style question about the current puzzle.' It clearly distinguishes from sibling tools: give_up_and_reveal ends the puzzle, start_session begins it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies when to use (to ask a yes/no question about the current puzzle) but does not provide explicit exclusions or when not to use. The context of siblings makes the usage clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It mentions the primary effects (reveal solution, end session) and a condition, but lacks details on irreversibility, permissions, or side effects. This is adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two efficient sentences convey the purpose, effect, and condition without any wasted words. The description is front-loaded and every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the tool is simple, the description omits what the 'hidden solution' actually is (e.g., structure, format) and does not clarify the unit for '60' (e.g., percent, points). No output schema exists, so the return value is not described. These gaps reduce completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single parameter (session_id), so the schema provides complete documentation. The description does not add any additional meaning or constraints beyond what the schema already describes.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reveals the hidden solution and ends the session, distinguishing it from sibling tools 'ask_question' and 'start_session'. The specific verb 'reveal' and resource 'solution' make the action unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear precondition ('Only allowed once solve progress reaches 60'), guiding when to use the tool. However, it does not explicitly mention alternatives or when not to use it, lowering the score slightly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the hidden solution stays on the server, which is key behavioral context. However, it does not mention whether starting a new session overwrites an existing one or any state management details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core action, and zero waste. Every piece of information is useful and presented efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description explains what is returned (surface story) and what is hidden. It lacks details on session lifecycle or error handling, but for a start tool, it covers the most important aspects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining the region options (CN/US/JP), difficulty choices (easy/hard), and keyword matching. This provides value beyond the schema field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it starts a new Turtle Soup puzzle session, returns the surface story, and hides the solution. It distinguishes itself from sibling tools (ask_question, give_up_and_reveal) by initiating the session, which is the primary purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description tells when to use the tool (to start a session) and mentions optional filters. It does not explicitly state when not to use or provide alternatives, but the sibling context implies this is the only start tool. Could be improved by noting that a session must be started before using siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.